Greetings fellow forum members, Our team is currently working with Solr 8.11 in cloud mode to power our search system, built using Java Spring at the application layer. We're facing a challenge in maintaining up-to-date pricing information for our ecommerce platform, which experiences frequent data changes throughout the day. While attempting to achieve real-time data updates, we've encountered issues related to Solr's latency and overall system performance.
As of now, we've implemented a process that halts data writes during the day. Instead, we retrieve updated pricing data from a separate microservice that maintains a cached and current version of the information. However, we believe this approach isn't ideal due to its potential impact on system efficiency. We're seeking guidance on designing an architecture that can seamlessly handle real-time updates to our Solr index without compromising the search latency that our users expect. Writing directly to Solr nodes appears to increase read latency, which is a concern for us. Our goal is to strike a balance between keeping our pricing information up-to-date and maintaining an acceptable level of system responsiveness. We would greatly appreciate any insights, strategies, or best practices from the community that can help us tackle this challenge. How can we optimize our approach to real-time data updates while ensuring Solr's latency remains within acceptable limits? Any advice or suggestions on architecture, techniques, or tools would be invaluable. Thank you in advance for your expertise and assistance. Regards, Neeraj giri
